Older people and the smart city: Developing inclusive practices to protect and serve a vulnerable population

Tupasela, Aaro; Devis Clavijo, Juanita; Salokannel, Marjut; Fink, Christoph Article Older people and the smart city: Developing inclusive practices to protect and serve a vulnerable population Internet Policy Review Provided in Cooperation with: Alexander von Humboldt Institute for Internet and Society (HIIG), Berlin Suggested Citation: Tupasela, Aaro; Devis Clavijo, Juanita; Salokannel, Marjut; Fink, Christoph (2023) : Older people and the smart city: Developing inclusive practices to protect and serve a vulnerable population, Internet Policy Review, ISSN 2197-6775, Alexander von Humboldt Institute for Internet and Society, Berlin, Vol. 12, Iss. 1, pp. 1-21, https://doi.org/10.14763/2023.1.1700 This Version is available at: https://hdl.handle.net/10419/271327 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/3.0/de/legalcode Volume 12 | Older people and the smart city – Developing inclusive practices to protect and serve a vulnerable population Aaro Tupasela University of Helsinki aaro[email protected] Juanita Devis Clavijo Amsterdam Institute for Advanced Metropolitan Solutions juanita.de[email protected] Marjut Salokannel University of Helsinki marjut[email protected] Christoph Fink University of Helsinki [email protected] DOI: https://doi.org/10.14763/2023.1.1700 Published: 31 March 2023 Received: 28 September 2022 Accepted: 22 November 2022 Funding: The research leading to these results has received funding from the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No. 101004590. Competing Interests: The author has declared that no competing interests exist that have influenced the text. Licence: This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 License (Germany) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. https://creativecommons.org/licenses/by/3.0/de/deed.en Copyright remains with the author(s). Citation: Tupasela, A. & Devis Clavijo, J. & Salokannel, M. & Fink, C. (2023). Older people and the smart city – Developing inclusive practices to protect and serve a vulnerable population. Internet Policy Review, 12(1). https://doi.org/10.14763/ 2023.1.1700 Keywords: Smart cities, Digital twins, Data protection, Privacy, Age-friendly cities Issue 1 Abstract: Despite increased interest in the development of smart cities and urban spaces that cater to the needs of their inhabitants, there is a significant lack of information and experience when it comes to working with older people. URBANAGE is a European H2020 project focused on supporting urban planners and policymakers in the decision-making process for age-friendly cities by developing new technologies for evidence-based decision-making. Older adults over 60 years of age, public servants and other relevant stakeholders were invited to co-create and test the solution to ensure that their needs and challenges were being addressed by the project. Decision-makers are facing major challenges in terms of understanding and addressing the needs of vulnerable population groups, such as older people, because of the lack of large enough datasets of disaggregated anonymised data. In this article, we report on the main challenges encountered during the implementation of the URBANAGE project, and the development of the components for big data analytics, visualisations, predictive algorithms and simulation. Using examples from three European locations – Helsinki, Flanders and Santander – we describe and discuss how we can gather personal data related to the daily lives of older people in terms of the existing privacy and data protection laws in the EU. The use of new technologies, such as location-based information devices, can provide up-to-date and precise information regarding problems that older people face while moving around the city, but they pose privacy concerns at the same time. This paper is part of Future-proofing the city: A human rights-based approach to governing algorithmic, biometric and smart city technologies, a special issue of Internet Policy Review guest-edited by Alina Wernick and Anna Artyushina. Introduction Europe, along with many other regions of the world, is facing an increase in its ageing population, and the challenges that come with it. According to some estimates, by 2050 the older population in Europe will increase by 39.3 million (Eurostat, 2020). At the same time, studies have noted that the rise in the proportion of older people in the total population has been accompanied by an increase in digital ageism, a new form of digital discrimination (Manor & Hersovici, 2021). These forms of discrimination may entail excluding older people from design considerations or as a potential user group of particular services. Digital ageism refers to the assumptions and stereotypes associated with the abilities of older people to use and learn to use digital technologies (Köttl & Mannheim, 2021). This trend poses new challenges for cities in developing services. In many cases, decisionmakers and planners see technology as one possible solution to many of the challenges associated with ageing. Such solutions include care robots and other smart technologies, such as self-tracking and monitoring devices to help in everyday life. The development of smart city technologies has become an increasingly salient feature in urban planning and development. The development of digital twins for cities has been one example of how cities are seeking to implement new approaches to planning and design. Urban planning seeks to include a broader spec- 2 Internet Policy Review 12(1) | 2023 trum of actors in the development and design process. This includes the development and use of data-driven evidence-based decision-making tools (Angelidou, 2016). In this article, we present the ongoing work that the URBANAGE project (Enhanced URBAN planning for AGE-friendly cities through disruptive technologies) is conducting. URBANAGE aims to assess the potential benefits, risks and impact of implementing a long-term sustainable framework for data-driven decision-making in the field of urban planning for age-friendly cities. Age-friendly refers to a more inclusive approach to city planning and development. Focusing on one type of vulnerable population allowed us to understand the specific needs of this target group. This model will be developed through an inclusive co-creation and testing strategy with relevant stakeholders (public servants) and users (older adults), based on a decision-support ecosystem that integrates multidimensional Big Data analysis, modelling and simulation with artificial intelligence (AI) algorithms, visualisation through Urban Digital Twins and gamification for enhanced engagement purposes. Based on a thorough understanding of users’ needs, the project will validate its findings by piloting use cases in three local planning systems in Europe (Helsinki, Santander, and Flanders) (URBANAGE, 2022). We focus on the use of inclusive co-creation processes used to develop and guide age-friendly urban planning, and also highlight some of the social, legal and ethical considerations that have arisen and been examined during the project thus far. Our work builds on and contributes to previous work on smart cities and citizen involvement by testing and implementing approaches and methods for including older people in planning and developing smart city technologies (Cardullo & Kitchin, 2018). More specifically, in this paper we focus on the legal aspects and concerns entailed in collecting and including data from older people to explore how an inclusive approach to planning and development can help to mitigate some of the risks associated with data collection. These approaches to inclusion are not new (cf. Arnstein, 1969), but require re-thinking some of the new technologies that are being developed and deployed in smart city development. The inclusion of older citizens in urban planning reflects an interest in respecting basic human rights, as well as being more inclusive in decision-making. The role of digital governance and human rights has become a point of interest more recently, with programmes such as the United Nations Human Settlements Programme (UN- Habitat) calling for improved representation and inclusivity in the development and implementation of digital technologies in cities (UN-Habitat, 2022). 3 Tupasela, Devis Clavijo, Salokannel, Fink The inclusion of older people in planning also recognises the concrete need to consider the rising costs associated with an ageing population, thereby pre-emp- tively seeking solutions that may mitigate future expenses through planning. Giv- en that urban planning and development are increasingly using and developing high-tech solutions and tools to help in planning, it is important to better understand how human rights, especially with reference to older people, need to be considered and respected. Given that demographic projections show that Europe’s ageing population will peak in the coming decades, developing age-friendly cities is all the more important. Addressing the needs and challenges of older people requires a non-traditional approach where multiple disciplines work together in developing holistic solutions for addressing the complexity of the urban environment. In the same way, new “disruptive” technologies are required to support such complex systems. The URBANAGE project aims to support civil servants in creating age-friendly initiatives by developing and piloting such new “disruptive” technologies. In particular, we examine the different needs and interests of three pilot locations: Helsinki, Santander and Flanders. In these three locations, we recruited a diverse, albeit small, group of older people for interviews and co-creation sessions. In addition, we conducted interviews with civil servants to discuss the challenges that they had identified in relation to inclusive planning that also considered the needs of older people. The three cases provide insights into the varying needs of the older population in these different locations, as well as the various capabilities and processes that are taking place in urban environments with different geographical and cultural specificities. Cities tend to have diverse capacities in relation to the data that they are able to collect (Ylipulli & Luusua, 2020; Walravenz et al., 2019; Díaz-Díaz et al., 2017), but access to and use of data on vulnerable populations can be particularly difficult to obtain. Common to all three locations, however, is an interest in making decision-making more inclusive, coupled with respect for human rights in the development and implementation of new technologies. Smart city initiatives have become prevalent during the past ten years, whereby cities see the increased use of digital technologies as the basis for improved decision-making and planning (Angelidou, 2017). At the same time, questions related to the increased datafication or intensification of data collection have renewed calls for discussions regarding rights and obligations, such as data justice (Wong et al., 2020; Dencik et al., 2019; Hoeyer 2016; Metcalf, 2015). These rights and obligations include the inclusion of affected populations in the design, development and implementation of new technologies. Our article is structured as follows. First, we will discuss some of the challenges 4 Internet Policy Review 12(1) | 2023 that cities face when addressing the needs and challenges of older people in the urban environment. Second, we will present the most salient features of the legal framework at the EU level, which has a bearing on urban planning. Third, we will discuss the development and use of different strategies to support civil servants in enabling age-friendly cities. Finally, we discuss the challenges and opportunities that relate to a rights-based approach to inclusive planning. Our paper concludes with a call for a more inclusive design and development approach for cities and civil servants as a robust way of mitigating rising costs. Challenges cities face when planning for older population groups Cities across the globe have been increasing the attention they pay to their residents’ well-being and flourishing as key factors in improving urban “liveability” (Cassarino et al., 2021). In part, this is a reaction to a perceived competition among cities to attract the brightest minds and most productive citizens, and therefore gain the best reputation (Florida & Mellander, 2015). Beyond that, it indicates a sincere ambition to provide all residents with the capability to “live a good life” (Lloyd-Sherlock, 2002), as called for in the United Nations Sustainable Development Goals (SDG) 3 (“Good health and well-being”), 10 (“Reduced inequalities”) and 11 (“Sustainable cities and communities”), for example. It is particularly with the latter motivation in mind that decision-makers and planners alike take a closer look at what could make their cities more just, more equitable and more liveable places for vulnerable groups such as children, low-income residents and older people, to name just a few (Derr et al., 2013). Although our research focus is specifically on older people, they share many common characteristics with other marginalised and vulnerable groups in that their voice and perspectives are often overlooked in the planning processes. Older people, despite representing a diverse and fuzzily delineated group, have become the focus of urban planners: their numbers are increasing (United Nations, 2019), and many of the challenges they encounter in their everyday lives could be averted or eased by appropriate urban interventions. For instance, many older people face challenges in realising their mobility needs, despite the ubiquitous opportunities of urban mobility. Accessing everyday places can be challenging for seniors, for instance, in a physical manner when it comes to long walking distances, poor infrastructure for active modes of transport or insufficient or inaccessible public transport. These factors also correspond to the most commonly voiced needs and wishes of older people participating in a series of focus groups de- 5 Tupasela, Devis Clavijo, Salokannel, Fink signed to inform the URBANAGE project. The social and psychological barriers to participating in local communities, in political and social life on an urban scale and to asking for assistance should not be underestimated either, but many factors that limit older people’s lives could be dramatically improved with concerted efforts to increase the quality of physical urban space. Cities, like most aspects of our lives, have undergone tremendous technological advancements in recent decades. Spatial data infrastructure(s) (SDE), once glorified centralised vaults of geospatial data accessible to all city departments, have evolved into smart city initiatives and digital urban twins: dynamic computer models mirror every detail of a city’s physical, organisational, and social realities to inform policymakers, planners and decision-makers “in real-time” – possibly forecasting the impact of anticipated decisions and changes. However, while not entirely positivist or a reduction of a city to a single perspective, smart city infrastructures share a critical limitation with other data science approaches: what cannot be measured, cannot be recorded. It is challenging to gather data on older people, or on other marginalised groups (Wang et al., 2021; Rose, 2020). Typically, the data collected and analysed emphasises the interests of the majority group. This is further aggravated by a legacy – among other things – of transport-planning models assuming a representative “average resident”, who often implicitly ends up being white, middle-aged, male and middle class. More often than not, neither the model nor the data take marginalised groups and the most vulnerable residents into consideration (Wang et al., 2021). However, the lack of data does not stem from disregard. There are concrete and tangible reasons and motivations, ranging from technological and practical to ethical and legal, why smart cities struggle to collect and provide data on older people. From a practical perspective, it is worth noting that older people are the least likely to engage in a digital lifestyle and thus do not leave a particularly strong footprint in the digital world. Data derived from social media, for instance, cannot provide insights into the daily itineraries of older people, nor can data from fitness trackers give estimates on older people’s walking or cycling speeds. These pieces of data often exist, but when disaggregated by age, samples become too small for analysis, or certain groups are overrepresented. Willberg et al. (2021), for instance, found that young men and “super-users” are overrepresented in bike-sharing data. Along the same lines, Heikinheimo et al. (2020) observed that active athletes generate the most data on Strava, a fitness-tracking app. In datasets obtained by statistical bureaus or other data providers, such as telecom operators, data is min- 6 Internet Policy Review 12(1) | 2023 imised and aggregated to protect rights to privacy and prevent unwanted individual identification. Minority groups are thus not visible in such data: a side effect of “privacy engineering” practices that aim to translate the vague concept of privacy into concrete requirements (Rommetveit & van Dijk, 2022). This is both legally and ethically desirable, but leaves planners without robust ways to guide their work. There is a growing consensus among scholars, practitioners and policymakers that urban planning and policy should strive to support their decisions with concrete evidence, also in order to improve residents’ acceptance of decisions that are almost always the outcome of complex mediation and negotiation processes between many competing interests (Krizek et al., 2009). It is imperative that this evidence includes the voices and perspectives of vulnerable groups, but currently data often fails to represent them appropriately. New data need to be collected or derived, but legal, technological and practical concerns also need to be considered. Legal questions related to gathering personal data from older people in terms of EU privacy and data protection laws The need for mobility-based data from older people in urban planning In her report on the enjoyment of all human rights by older persons, Mahler (2020, p. 6) highlights the problems relating to the lack of data on the everyday realities of older persons and their enjoyment of human rights. She emphasises that it is essential to have disaggregated data on older people for inclusive and effective public policy making. The problem is that it is difficult to obtain such data. One possible way is to collect mobility data on older people through smart devices. Such data are particularly sensitive, however. The devices link location data, environmental data and behavioural data with personal and physiological data, including healthspecific data (Mahler, 2020, p.10). Such data is impossible to anonymise at the municipal and country levels. Disaggregation of such data may still be possible, depending on the parameters used, if we could demonstrate that disaggregated data could be regarded as necessary to prove possible inequality and discrimination (Mahler, 2020, p. 8). The notion of disaggregative, anonymised data presupposes that anonymised data sets exist. However, when data collected through IoT devices comprises location data and can be linked to other data sources, anonymisation becomes virtually impossible. Farzanehfar et al. (2021) has shown that by using three months' worth of 7 Tupasela, Devis Clavijo, Salokannel, Fink location data, 93% of people are uniquely identifiable in a population of 60 million, using four points of auxiliary information. In the following section, we analyse the process for gathering personal data about older people and their daily activities from the perspective of the EU’s existing privacy and data protection laws. While recognising that properly anonymised disaggregated-level data would be the best method for urban planning, it may be extremely challenging given the sensitivity of mobility data. In the following, we explore to what extent data anonymisation could be utilised in urban planning, and which legal basis, in terms of gathering personal data from older people, could be utilised in data protection law. Collection of mobility data in the URBANAGE use cases In the URBANAGE use cases, the limited number of participants made any type of anonymisation process impossible. The GDPR defines personal data as encompassing both directly and indirectly identifiable data.1 Any information relating to an identified or identifiable natural person is to be considered personal information. To determine whether a certain person is identifiable, an account should be taken of all the means likely to be used, such as singling out, either by a controller or by another person, to identify the natural person directly or indirectly (Recital 26, GDPR). This means that even if a person cannot be identified by name, but that person can be pointed out in a crowd due to their mobility patterns, then the data relating to that person is personal data and subject to the GDPR. In addition to physical locations, location data from smartphones can also reveal interactions with other people. Thus, location data can be regarded as one of the most sensitive types of data (de Montjoye, 2013; EDPB/EDPS Joint opinion, 2022). Older people are not explicitly afforded special protection in EU privacy laws. However, Article 21 of the EU Charter of Fundamental Rights prohibits discrimination based on age, among other factors. The EU General Data Protection Regulation (GDPR) affords strengthened protection for certain sensitive groups of personal data, namely data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs or trade union membership, as well as genetic data, biometric data for the purpose of uniquely identifying a natural person, data concerning health or data concerning a 1. According to Article 4.1 (1) ‘“personal data”’ means any information relating to an identified or identifiable natural person (‘“data subject”’); an identifiable natural person is one who can be identified, directly or indirectly, in particular by reference to an identifier such as a name, an identification number, location data, an online identifier or to one or more factors specific to the physical, physiological, genetic, mental, economic, cultural or social identity of that natural person. 8 Internet Policy Review 12(1) | 2023 of the three pilots, based on the technical feasibility and available data sources, then developed an implementation plan. Each pilot decided to implement two complementary solutions: one solution tailored for civil servants and the other for the older citizens. The first solution consisted of the development of an urban digital twin to support civil servants in the age-friendly data-driven decision process. Two pilots (Flanders and Santander) developed a solution to support older people in navigating the city. The Helsinki pilot proposed a solution focusing on the use of IoT devices to collect data about the end-user’s perception of the urban environments. In all of the pilot implementation plans, it was clear that the available data sources were not sufficient to inform the designed solutions, due to a lack of disaggregated and anonymised location data. In some cases, this was because data providers did not collect information about specific segments of the population (e.g., age). In others, as in the case of the Flanders pilot, the law prohibited the data processor from accessing personal records and conducting anonymisation processes. Moreover, even when allowed, the legal and anonymisation procedures were too complex to be performed in the context of the project implementation. Finally, other types of open data (e.g., accessibility data) were not available in the required data format (e.g., pdf, cad files) and they could not be linked with other GIS data (e.g., roads, buildings). As a result of this analysis, all the pilots decided to integrate an additional data collection process as a part of the application tailored to older citizens. This required the older citizens to provide consent for the collection and processing of their personal data for the purposes described. Although the Covid-19 pandemic accelerated internet usage and technology adoption among the older population (Sixsmith et al., 2022), older citizens are increasingly more prone to cybersecurity concerns and scams because of their lack of digital skills and competences (Nicholson et al., 2019). This issue shows how technology adoption per se is not sufficient and needs to be supported by technology that is designed to be understandable and explainable. In this phase, the co-creation methodologies played an additional fundamental role in educating the end users about the data collected, the processing procedures and their implications. This step was crucial in gaining trust in the transparency of the proposed solution, and hence in favouring its adoption. This was achieved by integrating trustability and transparency as a part of the requirements 15 Tupasela, Devis Clavijo, Salokannel, Fink in the early phases of design and development. Special attention has been devoted to the creation of dedicated consent forms that took into account the lack of digital proficiency by making them easy to understand for the end users. This iterative process also addresses more general aspects concerning the explainability of the technology (Helbing et al., 2021). Given the inputs collected in these phases, the pilots are now proceeding in the development phase. Further testing activities with end users are foreseen during the different intermediate steps of the development, to inform them about, and help them adapt, to the subsequent iterations, with a view to informed and educated adoption. Challenges of inclusive rights-based urban decision-making With the rise of smart city technologies, the possibilities afforded to data collection and use in decision-making tools are increasing considerably. At the same time, GDPR and other legislation impose specific requirements on the legal basis for data collection and storage. The collection of data from vulnerable groups, such as older people, poses further challenges in that vulnerable groups ought to be afforded special protection. At the same time, data collection is essential in helping to identify ways in which the needs of vulnerable groups can be met. Current approaches to data collection tend to view informed consent as a technical and legal process in which engagement with the data subject is minimised to formalised forms and documents. One of the goals of the URBANAGE project has been to highlight the robustness of ongoing engagement through processes of cocreation and testing. An example of the strength of this approach relates to difficulties in the anonymisation of location data. Location data can prove to be sensitive in nature despite the best efforts to try to anonymise data. Consequently, the co-creation process used in the pilots helped to provide crucial information for developers on the possible privacy trade-offs and concerns that vulnerable groups may have regarding the use of such data. At the same time, the co-creation process also allowed the older participants time to ask questions and reflect on the nuances associated with location data and privacy. Although co-creation may not be scalable in relation to large datasets, using this approach with smaller focus groups and pilot studies can help to identify possible concerns, as well as provide an important engagement opportunity with vulnerable and marginalised communities. Although urban decision-making may not necessarily need high resolution in planning and develop- 16 Internet Policy Review 12(1) | 2023 ment, the process of engaging vulnerable groups helps to provide important insights that can be used in planning cities that are more inclusive. In the Flemish pilot, the outcomes of the co-creation workshops, together with the implementation challenges, provided meaningful insights for the cities and the region about how to develop their data platform to support age-friendly initiatives. During the early development phase of scoping for technologies, the Flemish developers understood that the collection of sensitive health data was not necessary for developing their pilot. Consequently, instead of seeking to collect sensitive health data, the pilot sought to ask users what types of outdoor environments they preferred to spend time in. This approach led to the development of an application in which users can anonymously identify outdoor areas that are shady and pleasant on hot summer days. Although the URBANAGE project has focused on older individuals, their approach can be useful for other stakeholders, regardless of age or possible vulnerability. The co-creation sessions organised in the three locations also allowed city planners to better understand the concerns and questions that older people may have with regard to privacy. For example, given the possible benefits that the research may provide, certain types of data collection or tracking were considered acceptable. As such, engagement with older people also provided important opportunities to better understand and implement design-based approaches to data protection (Rommetveit & van Dijk, 2022). Current legislation requires that end users be able to understand the risks associated with any type of data collection. Given that the collection of location data – even when collected using a non-identifiable device – can lead to the identification of individuals, it is of utmost importance to explain and discuss these challenges in a transparent manner. This approach shows respect for participants and allows them to discuss and present any concerns or questions they might have. This is also an important form of empowerment for otherwise marginalised groups, such as older people. Although smart city technologies rely heavily on automation for data collection and processing, the URBANAGE project highlights the need for and importance of human engagement in planning and development (Helbing et al., 2021). This is particularly important with regard to vulnerable populations such as older people. Although different cities have vastly different data collection capabilities and smart city implementations (Ylipulli & Luusua, 2020; Walravenz et al., 2019; Díaz- Díaz et al., 2017), this project has highlighted how co-creation can be used in multiple different contexts to better understand the needs of the older population. 17 Tupasela, Devis Clavijo, Salokannel, Fink Conclusion With the URBANAGE project, we provide an example of how data from older people can be collected and used to inform age-friendly and inclusive decision-mak- ing tools. Although the scaling of data collection poses challenges for co-creation, our study suggests that co-creation is an excellent and feasible approach when piloting new studies and developing technologies that support the real needs of inhabitants and civil servants. In many countries and cities which strive to adopt smart city technologies, data remains in silos, which poses a challenge for more effective data analysis regarding vulnerable population groups, such as older people. Current trends which emphasise data justice and data self-determination suggest that engagement with study populations can help address participants’ concerns, especially when working with vulnerable population groups. Co-creation and engagement practices provide important benefits with regard to concerns over transparency, consent and anonymisation. When new technologies are used – such as location-based data collection – concerns may be raised regarding privacy and anonymity, and creating and maintaining spaces for dialogue. The co-creation sessions in the URBANAGE project help to address some of these issues. 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